6 citations · 6 across the 4 of their papers we have counts for
5 papers
Learning Time-Series Representations by Hierarchical Uniformity-Tolerance Latent Balancing
Amin Jalali, Milad Soltany, Michael Greenspan +1
We propose TimeHUT, a novel method for learning time-series representations by hierarchical uniformity-tolerance balancing of contrastive representations. Our method uses two disti…
Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training
Milad Soltany, Farhad Pourpanah, Mahdiyar Molahasani +2
In this paper, we propose a novel approach, Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training (FedSB), to address the challenges of data hete…
Federated Unsupervised Domain Generalization using Global and Local Alignment of Gradients
Farhad Pourpanah, Mahdiyar Molahasani, Milad Soltany +2
We address the problem of federated domain generalization in an unsupervised setting for the first time. We first theoretically establish a connection between domain shift and alig…
An intelligent modular real-time vision-based system for environment perception
Amirhossein Kazerouni, Amirhossein Heydarian, Milad Soltany +3
A significant portion of driving hazards is caused by human error and disregard for local driving regulations; Consequently, an intelligent assistance system can be beneficial. Thi…
HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation
Moein Heidari, Amirhossein Kazerouni, Milad Soltany +4
Convolutional neural networks (CNNs) have been the consensus for medical image segmentation tasks. However, they suffer from the limitation in modeling long-range dependencies and…